youtube_covid.ipynb

{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importando as bibliotecas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import geopandas as gpd\n",
    "import matplotlib.pyplot as plt"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Abrindo a pasta dos arquivos baixados"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "391\n"
     ]
    }
   ],
   "source": [
    "caminho_covid = 'C:/Users/joaovitor/Desktop/Dados'\n",
    "\n",
    "lista = os.listdir(caminho_covid)\n",
    "print(len(lista))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Dando uma olhada nos arquivos presentes na pasta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "covid_02_26.cpg\n",
      "covid_02_26.dbf\n",
      "covid_02_26.prj\n",
      "covid_02_26.sbn\n",
      "covid_02_26.sbx\n",
      "covid_02_26.shp\n",
      "covid_02_26.shp.xml\n",
      "covid_02_26.shx\n",
      "covid_02_27.cpg\n",
      "covid_02_27.dbf\n",
      "covid_02_27.prj\n",
      "covid_02_27.sbn\n",
      "covid_02_27.sbx\n",
      "covid_02_27.shp\n",
      "covid_02_27.shp.xml\n",
      "covid_02_27.shx\n",
      "covid_02_28.cpg\n",
      "covid_02_28.dbf\n",
      "covid_02_28.prj\n",
      "covid_02_28.sbn\n",
      "covid_02_28.sbx\n",
      "covid_02_28.shp\n",
      "covid_02_28.shp.xml\n",
      "covid_02_28.shx\n",
      "covid_02_29.cpg\n",
      "covid_02_29.dbf\n",
      "covid_02_29.prj\n",
      "covid_02_29.sbn\n",
      "covid_02_29.sbx\n",
      "covid_02_29.shp\n",
      "covid_02_29.shp.xml\n",
      "covid_02_29.shx\n",
      "covid_03_01.cpg\n",
      "covid_03_01.dbf\n",
      "covid_03_01.prj\n",
      "covid_03_01.sbn\n",
      "covid_03_01.sbx\n",
      "covid_03_01.shp\n",
      "covid_03_01.shp.xml\n",
      "covid_03_01.shx\n",
      "covid_03_02.cpg\n",
      "covid_03_02.dbf\n",
      "covid_03_02.prj\n",
      "covid_03_02.sbn\n",
      "covid_03_02.sbx\n",
      "covid_03_02.shp\n",
      "covid_03_02.shp.xml\n",
      "covid_03_02.shx\n",
      "covid_03_03.cpg\n",
      "covid_03_03.dbf\n",
      "covid_03_03.prj\n",
      "covid_03_03.sbn\n",
      "covid_03_03.sbx\n",
      "covid_03_03.shp\n",
      "covid_03_03.shp.xml\n",
      "covid_03_03.shx\n",
      "covid_03_04.cpg\n",
      "covid_03_04.dbf\n",
      "covid_03_04.prj\n",
      "covid_03_04.sbn\n",
      "covid_03_04.sbx\n",
      "covid_03_04.shp\n",
      "covid_03_04.shp.xml\n",
      "covid_03_04.shx\n",
      "covid_03_05.cpg\n",
      "covid_03_05.dbf\n",
      "covid_03_05.prj\n",
      "covid_03_05.sbn\n",
      "covid_03_05.sbx\n",
      "covid_03_05.shp\n",
      "covid_03_05.shp.xml\n",
      "covid_03_05.shx\n",
      "covid_03_06.cpg\n",
      "covid_03_06.dbf\n",
      "covid_03_06.prj\n",
      "covid_03_06.sbn\n",
      "covid_03_06.sbx\n",
      "covid_03_06.shp\n",
      "covid_03_06.shp.xml\n",
      "covid_03_06.shx\n",
      "covid_03_07.CPG\n",
      "covid_03_07.dbf\n",
      "covid_03_07.prj\n",
      "covid_03_07.sbn\n",
      "covid_03_07.sbx\n",
      "covid_03_07.shp\n",
      "covid_03_07.shp.xml\n",
      "covid_03_07.shx\n",
      "covid_03_08.CPG\n",
      "covid_03_08.dbf\n",
      "covid_03_08.prj\n",
      "covid_03_08.sbn\n",
      "covid_03_08.sbx\n",
      "covid_03_08.shp\n",
      "covid_03_08.shp.xml\n",
      "covid_03_08.shx\n",
      "covid_03_09.cpg\n",
      "covid_03_09.dbf\n",
      "covid_03_09.prj\n",
      "covid_03_09.sbn\n",
      "covid_03_09.sbx\n",
      "covid_03_09.shp\n",
      "covid_03_09.shp.xml\n",
      "covid_03_09.shx\n",
      "covid_03_10.cpg\n",
      "covid_03_10.dbf\n",
      "covid_03_10.prj\n",
      "covid_03_10.sbn\n",
      "covid_03_10.sbx\n",
      "covid_03_10.shp\n",
      "covid_03_10.shp.xml\n",
      "covid_03_10.shx\n",
      "covid_03_11.cpg\n",
      "covid_03_11.dbf\n",
      "covid_03_11.prj\n",
      "covid_03_11.sbn\n",
      "covid_03_11.sbx\n",
      "covid_03_11.shp\n",
      "covid_03_11.shp.xml\n",
      "covid_03_11.shx\n",
      "covid_03_12.cpg\n",
      "covid_03_12.dbf\n",
      "covid_03_12.prj\n",
      "covid_03_12.sbn\n",
      "covid_03_12.sbx\n",
      "covid_03_12.shp\n",
      "covid_03_12.shp.xml\n",
      "covid_03_12.shx\n",
      "covid_03_13.cpg\n",
      "covid_03_13.dbf\n",
      "covid_03_13.prj\n",
      "covid_03_13.sbn\n",
      "covid_03_13.sbx\n",
      "covid_03_13.shp\n",
      "covid_03_13.shp.xml\n",
      "covid_03_13.shx\n",
      "covid_03_14.cpg\n",
      "covid_03_14.dbf\n",
      "covid_03_14.prj\n",
      "covid_03_14.sbn\n",
      "covid_03_14.sbx\n",
      "covid_03_14.shp\n",
      "covid_03_14.shp.xml\n",
      "covid_03_14.shx\n",
      "covid_03_15.cpg\n",
      "covid_03_15.dbf\n",
      "covid_03_15.prj\n",
      "covid_03_15.sbn\n",
      "covid_03_15.sbx\n",
      "covid_03_15.shp\n",
      "covid_03_15.shp.xml\n",
      "covid_03_15.shx\n",
      "covid_03_16.cpg\n",
      "covid_03_16.dbf\n",
      "covid_03_16.prj\n",
      "covid_03_16.sbn\n",
      "covid_03_16.sbx\n",
      "covid_03_16.shp\n",
      "covid_03_16.shp.xml\n",
      "covid_03_16.shx\n",
      "covid_03_17.cpg\n",
      "covid_03_17.dbf\n",
      "covid_03_17.prj\n",
      "covid_03_17.sbn\n",
      "covid_03_17.sbx\n",
      "covid_03_17.shp\n",
      "covid_03_17.shp.xml\n",
      "covid_03_17.shx\n",
      "covid_03_18.cpg\n",
      "covid_03_18.dbf\n",
      "covid_03_18.prj\n",
      "covid_03_18.sbn\n",
      "covid_03_18.sbx\n",
      "covid_03_18.shp\n",
      "covid_03_18.shp.xml\n",
      "covid_03_18.shx\n",
      "covid_03_19.cpg\n",
      "covid_03_19.dbf\n",
      "covid_03_19.prj\n",
      "covid_03_19.sbn\n",
      "covid_03_19.sbx\n",
      "covid_03_19.shp\n",
      "covid_03_19.shp.xml\n",
      "covid_03_19.shx\n",
      "covid_03_20.cpg\n",
      "covid_03_20.dbf\n",
      "covid_03_20.prj\n",
      "covid_03_20.sbn\n",
      "covid_03_20.sbx\n",
      "covid_03_20.shp\n",
      "covid_03_20.shp.xml\n",
      "covid_03_20.shx\n",
      "covid_03_21.cpg\n",
      "covid_03_21.dbf\n",
      "covid_03_21.prj\n",
      "covid_03_21.sbn\n",
      "covid_03_21.sbx\n",
      "covid_03_21.shp\n",
      "covid_03_21.shp.xml\n",
      "covid_03_21.shx\n",
      "covid_03_22.cpg\n",
      "covid_03_22.dbf\n",
      "covid_03_22.prj\n",
      "covid_03_22.sbn\n",
      "covid_03_22.sbx\n",
      "covid_03_22.shp\n",
      "covid_03_22.shx\n",
      "covid_03_23.cpg\n",
      "covid_03_23.dbf\n",
      "covid_03_23.prj\n",
      "covid_03_23.sbn\n",
      "covid_03_23.sbx\n",
      "covid_03_23.shp\n",
      "covid_03_23.shp.xml\n",
      "covid_03_23.shx\n",
      "covid_03_24.cpg\n",
      "covid_03_24.dbf\n",
      "covid_03_24.prj\n",
      "covid_03_24.sbn\n",
      "covid_03_24.sbx\n",
      "covid_03_24.shp\n",
      "covid_03_24.shp.xml\n",
      "covid_03_24.shx\n",
      "covid_03_25.cpg\n",
      "covid_03_25.dbf\n",
      "covid_03_25.prj\n",
      "covid_03_25.sbn\n",
      "covid_03_25.sbx\n",
      "covid_03_25.shp\n",
      "covid_03_25.shp.xml\n",
      "covid_03_25.shx\n",
      "covid_03_26.cpg\n",
      "covid_03_26.dbf\n",
      "covid_03_26.prj\n",
      "covid_03_26.sbn\n",
      "covid_03_26.sbx\n",
      "covid_03_26.shp\n",
      "covid_03_26.shp.xml\n",
      "covid_03_26.shx\n",
      "covid_03_27.cpg\n",
      "covid_03_27.dbf\n",
      "covid_03_27.prj\n",
      "covid_03_27.sbn\n",
      "covid_03_27.sbx\n",
      "covid_03_27.shp\n",
      "covid_03_27.shp.xml\n",
      "covid_03_27.shx\n",
      "covid_03_28.cpg\n",
      "covid_03_28.dbf\n",
      "covid_03_28.prj\n",
      "covid_03_28.sbn\n",
      "covid_03_28.sbx\n",
      "covid_03_28.shp\n",
      "covid_03_28.shp.xml\n",
      "covid_03_28.shx\n",
      "covid_03_29.cpg\n",
      "covid_03_29.dbf\n",
      "covid_03_29.prj\n",
      "covid_03_29.sbn\n",
      "covid_03_29.sbx\n",
      "covid_03_29.shp\n",
      "covid_03_29.shp.xml\n",
      "covid_03_29.shx\n",
      "covid_03_30.cpg\n",
      "covid_03_30.dbf\n",
      "covid_03_30.prj\n",
      "covid_03_30.sbn\n",
      "covid_03_30.sbx\n",
      "covid_03_30.shp\n",
      "covid_03_30.shp.xml\n",
      "covid_03_30.shx\n",
      "covid_03_31.cpg\n",
      "covid_03_31.dbf\n",
      "covid_03_31.prj\n",
      "covid_03_31.sbn\n",
      "covid_03_31.sbx\n",
      "covid_03_31.shp\n",
      "covid_03_31.shp.xml\n",
      "covid_03_31.shx\n",
      "covid_04_01.cpg\n",
      "covid_04_01.dbf\n",
      "covid_04_01.prj\n",
      "covid_04_01.sbn\n",
      "covid_04_01.sbx\n",
      "covid_04_01.shp\n",
      "covid_04_01.shp.xml\n",
      "covid_04_01.shx\n",
      "covid_04_02.cpg\n",
      "covid_04_02.dbf\n",
      "covid_04_02.prj\n",
      "covid_04_02.sbn\n",
      "covid_04_02.sbx\n",
      "covid_04_02.shp\n",
      "covid_04_02.shp.xml\n",
      "covid_04_02.shx\n",
      "covid_04_03.cpg\n",
      "covid_04_03.dbf\n",
      "covid_04_03.prj\n",
      "covid_04_03.sbn\n",
      "covid_04_03.sbx\n",
      "covid_04_03.shp\n",
      "covid_04_03.shp.xml\n",
      "covid_04_03.shx\n",
      "covid_04_04.dbf\n",
      "covid_04_04.prj\n",
      "covid_04_04.shp\n",
      "covid_04_04.shx\n",
      "covid_04_05.dbf\n",
      "covid_04_05.prj\n",
      "covid_04_05.shp\n",
      "covid_04_05.shx\n",
      "covid_04_06.dbf\n",
      "covid_04_06.prj\n",
      "covid_04_06.shp\n",
      "covid_04_06.shx\n",
      "covid_04_07.dbf\n",
      "covid_04_07.prj\n",
      "covid_04_07.shp\n",
      "covid_04_07.shx\n",
      "covid_04_08.dbf\n",
      "covid_04_08.prj\n",
      "covid_04_08.shp\n",
      "covid_04_08.shx\n",
      "covid_04_09.dbf\n",
      "covid_04_09.prj\n",
      "covid_04_09.sbn\n",
      "covid_04_09.sbx\n",
      "covid_04_09.shp\n",
      "covid_04_09.shx\n",
      "covid_04_10.dbf\n",
      "covid_04_10.prj\n",
      "covid_04_10.shp\n",
      "covid_04_10.shx\n",
      "covid_04_11.dbf\n",
      "covid_04_11.prj\n",
      "covid_04_11.shp\n",
      "covid_04_11.shx\n",
      "covid_04_12.dbf\n",
      "covid_04_12.prj\n",
      "covid_04_12.shp\n",
      "covid_04_12.shx\n",
      "covid_04_13.dbf\n",
      "covid_04_13.prj\n",
      "covid_04_13.shp\n",
      "covid_04_13.shx\n",
      "covid_04_14.dbf\n",
      "covid_04_14.prj\n",
      "covid_04_14.shp\n",
      "covid_04_14.shx\n",
      "covid_04_15.cpg\n",
      "covid_04_15.dbf\n",
      "covid_04_15.prj\n",
      "covid_04_15.shp\n",
      "covid_04_15.shp.xml\n",
      "covid_04_15.shx\n",
      "covid_04_16.dbf\n",
      "covid_04_16.prj\n",
      "covid_04_16.shp\n",
      "covid_04_16.shx\n",
      "covid_04_17.dbf\n",
      "covid_04_17.prj\n",
      "covid_04_17.shp\n",
      "covid_04_17.shx\n",
      "covid_04_18.dbf\n",
      "covid_04_18.prj\n",
      "covid_04_18.shp\n",
      "covid_04_18.shx\n",
      "covid_04_19.dbf\n",
      "covid_04_19.prj\n",
      "covid_04_19.shp\n",
      "covid_04_19.shx\n",
      "covid_04_20.dbf\n",
      "covid_04_20.prj\n",
      "covid_04_20.shp\n",
      "covid_04_20.shx\n",
      "covid_04_21.dbf\n",
      "covid_04_21.prj\n",
      "covid_04_21.shp\n",
      "covid_04_21.shx\n",
      "covid_04_22.dbf\n",
      "covid_04_22.prj\n",
      "covid_04_22.shp\n",
      "covid_04_22.shx\n",
      "covid_04_23.dbf\n",
      "covid_04_23.prj\n",
      "covid_04_23.shp\n",
      "covid_04_23.shx\n",
      "covid_04_24.dbf\n",
      "covid_04_24.prj\n",
      "covid_04_24.shp\n",
      "covid_04_24.shx\n"
     ]
    }
   ],
   "source": [
    "for i in lista:\n",
    "    print(i) #queremos apenas os arquivos .shp , sem o .xml no final"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Pegando apenas os arquivos .shp da minha pasta"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "['covid_02_26.shp', 'covid_02_27.shp', 'covid_02_28.shp', 'covid_02_29.shp', 'covid_03_01.shp', 'covid_03_02.shp', 'covid_03_03.shp', 'covid_03_04.shp', 'covid_03_05.shp', 'covid_03_06.shp', 'covid_03_07.shp', 'covid_03_08.shp', 'covid_03_09.shp', 'covid_03_10.shp', 'covid_03_11.shp', 'covid_03_12.shp', 'covid_03_13.shp', 'covid_03_14.shp', 'covid_03_15.shp', 'covid_03_16.shp', 'covid_03_17.shp', 'covid_03_18.shp', 'covid_03_19.shp', 'covid_03_20.shp', 'covid_03_21.shp', 'covid_03_22.shp', 'covid_03_23.shp', 'covid_03_24.shp', 'covid_03_25.shp', 'covid_03_26.shp', 'covid_03_27.shp', 'covid_03_28.shp', 'covid_03_29.shp', 'covid_03_30.shp', 'covid_03_31.shp', 'covid_04_01.shp', 'covid_04_02.shp', 'covid_04_03.shp', 'covid_04_04.shp', 'covid_04_05.shp', 'covid_04_06.shp', 'covid_04_07.shp', 'covid_04_08.shp', 'covid_04_09.shp', 'covid_04_10.shp', 'covid_04_11.shp', 'covid_04_12.shp', 'covid_04_13.shp', 'covid_04_14.shp', 'covid_04_15.shp', 'covid_04_16.shp', 'covid_04_17.shp', 'covid_04_18.shp', 'covid_04_19.shp', 'covid_04_20.shp', 'covid_04_21.shp', 'covid_04_22.shp', 'covid_04_23.shp', 'covid_04_24.shp']\n",
      "==================\n",
      "59\n"
     ]
    }
   ],
   "source": [
    "lista_shp = []\n",
    "for i in lista:\n",
    "    if '.shp' in i:\n",
    "        if '.xml' in i:\n",
    "            pass\n",
    "        else:\n",
    "            lista_shp.append(i)\n",
    "print(lista_shp)\n",
    "print('==================')\n",
    "print(len(lista_shp))"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualizando a tabela com os dados para apenas 1 dia, para exemplificar"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>NM_ESTADO</th>\n",
       "      <th>NM_REGIAO</th>\n",
       "      <th>CD_GEOCUF</th>\n",
       "      <th>PAIS</th>\n",
       "      <th>ibge_code</th>\n",
       "      <th>city</th>\n",
       "      <th>date</th>\n",
       "      <th>state</th>\n",
       "      <th>confirmed</th>\n",
       "      <th>deaths</th>\n",
       "      <th>estpop2019</th>\n",
       "      <th>conf_rate</th>\n",
       "      <th>death_rate</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>SERGIPE</td>\n",
       "      <td>NORDESTE</td>\n",
       "      <td>28</td>\n",
       "      <td>BRASIL</td>\n",
       "      <td>2805703.0</td>\n",
       "      <td>Propriá</td>\n",
       "      <td>2020-04-06</td>\n",
       "      <td>SE</td>\n",
       "      <td>2</td>\n",
       "      <td>0.0</td>\n",
       "      <td>29626</td>\n",
       "      <td>6.75083</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (-36.80311 -10.24540)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>SERGIPE</td>\n",
       "      <td>NORDESTE</td>\n",
       "      <td>28</td>\n",
       "      <td>BRASIL</td>\n",
       "      <td>2802908.0</td>\n",
       "      <td>Itabaiana</td>\n",
       "      <td>2020-04-06</td>\n",
       "      <td>SE</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>95427</td>\n",
       "      <td>1.04792</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (-37.42163 -10.68559)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>SERGIPE</td>\n",
       "      <td>NORDESTE</td>\n",
       "      <td>28</td>\n",
       "      <td>BRASIL</td>\n",
       "      <td>2801306.0</td>\n",
       "      <td>Capela</td>\n",
       "      <td>2020-04-06</td>\n",
       "      <td>SE</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>34213</td>\n",
       "      <td>2.92287</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (-37.03634 -10.46875)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>SERGIPE</td>\n",
       "      <td>NORDESTE</td>\n",
       "      <td>28</td>\n",
       "      <td>BRASIL</td>\n",
       "      <td>2800308.0</td>\n",
       "      <td>Aracaju</td>\n",
       "      <td>2020-04-06</td>\n",
       "      <td>SE</td>\n",
       "      <td>27</td>\n",
       "      <td>3.0</td>\n",
       "      <td>657013</td>\n",
       "      <td>4.10951</td>\n",
       "      <td>0.1111</td>\n",
       "      <td>POINT (-37.09491 -10.99420)</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>SERGIPE</td>\n",
       "      <td>NORDESTE</td>\n",
       "      <td>28</td>\n",
       "      <td>BRASIL</td>\n",
       "      <td>2804508.0</td>\n",
       "      <td>Nossa Senhora da Glória</td>\n",
       "      <td>2020-04-06</td>\n",
       "      <td>SE</td>\n",
       "      <td>1</td>\n",
       "      <td>0.0</td>\n",
       "      <td>36924</td>\n",
       "      <td>2.70827</td>\n",
       "      <td>NaN</td>\n",
       "      <td>POINT (-37.52804 -10.17774)</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  NM_ESTADO NM_REGIAO CD_GEOCUF    PAIS  ibge_code                     city  \\\n",
       "0   SERGIPE  NORDESTE        28  BRASIL  2805703.0                  Propriá   \n",
       "1   SERGIPE  NORDESTE        28  BRASIL  2802908.0                Itabaiana   \n",
       "2   SERGIPE  NORDESTE        28  BRASIL  2801306.0                   Capela   \n",
       "3   SERGIPE  NORDESTE        28  BRASIL  2800308.0                  Aracaju   \n",
       "4   SERGIPE  NORDESTE        28  BRASIL  2804508.0  Nossa Senhora da Glória   \n",
       "\n",
       "         date state  confirmed  deaths  estpop2019  conf_rate  death_rate  \\\n",
       "0  2020-04-06    SE          2     0.0       29626    6.75083         NaN   \n",
       "1  2020-04-06    SE          1     0.0       95427    1.04792         NaN   \n",
       "2  2020-04-06    SE          1     0.0       34213    2.92287         NaN   \n",
       "3  2020-04-06    SE         27     3.0      657013    4.10951      0.1111   \n",
       "4  2020-04-06    SE          1     0.0       36924    2.70827         NaN   \n",
       "\n",
       "                      geometry  \n",
       "0  POINT (-36.80311 -10.24540)  \n",
       "1  POINT (-37.42163 -10.68559)  \n",
       "2  POINT (-37.03634 -10.46875)  \n",
       "3  POINT (-37.09491 -10.99420)  \n",
       "4  POINT (-37.52804 -10.17774)  "
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tabela_exemplo = gpd.read_file(os.path.join(caminho_covid, lista_shp[40]))\n",
    "tabela_exemplo.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exibindo os dados geográficos"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "tabela_exemplo.plot(figsize=(15,10), color='red', markersize=15)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Importando o mapa do Brasil"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/html": [
       "<div>\n",
       "<style scoped>\n",
       "    .dataframe tbody tr th:only-of-type {\n",
       "        vertical-align: middle;\n",
       "    }\n",
       "\n",
       "    .dataframe tbody tr th {\n",
       "        vertical-align: top;\n",
       "    }\n",
       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>ID_0</th>\n",
       "      <th>ISO</th>\n",
       "      <th>NAME_0</th>\n",
       "      <th>ID_1</th>\n",
       "      <th>NAME_1</th>\n",
       "      <th>HASC_1</th>\n",
       "      <th>CCN_1</th>\n",
       "      <th>CCA_1</th>\n",
       "      <th>TYPE_1</th>\n",
       "      <th>ENGTYPE_1</th>\n",
       "      <th>NL_NAME_1</th>\n",
       "      <th>VARNAME_1</th>\n",
       "      <th>geometry</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>33</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>1</td>\n",
       "      <td>Acre</td>\n",
       "      <td>BR.AC</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>Estado</td>\n",
       "      <td>State</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>POLYGON ((-73.33251 -7.32488, -73.27482 -7.350...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>33</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>2</td>\n",
       "      <td>Alagoas</td>\n",
       "      <td>BR.AL</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>Estado</td>\n",
       "      <td>State</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-35.90153 -9.86180, -35.90153 ...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>33</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>3</td>\n",
       "      <td>Amapá</td>\n",
       "      <td>BR.AP</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>Estado</td>\n",
       "      <td>State</td>\n",
       "      <td>None</td>\n",
       "      <td>None</td>\n",
       "      <td>MULTIPOLYGON (((-50.02403 0.85986, -50.02403 0...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>33</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>4</td>\n",
       "      <td>Amazonas</td>\n",
       "      <td>BR.AM</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>Estado</td>\n",
       "      <td>State</td>\n",
       "      <td>None</td>\n",
       "      <td>Amazone</td>\n",
       "      <td>POLYGON ((-67.32623 2.02968, -67.30118 1.92997...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>33</td>\n",
       "      <td>BRA</td>\n",
       "      <td>Brazil</td>\n",
       "      <td>5</td>\n",
       "      <td>Bahia</td>\n",
       "      <td>BR.BA</td>\n",
       "      <td>0</td>\n",
       "      <td>None</td>\n",
       "      <td>Estado</td>\n",
       "      <td>State</td>\n",
       "      <td>None</td>\n",
       "      <td>Ba¡a</td>\n",
       "      <td>MULTIPOLYGON (((-38.69708 -17.97903, -38.69708...</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   ID_0  ISO  NAME_0  ID_1    NAME_1 HASC_1  CCN_1 CCA_1  TYPE_1 ENGTYPE_1  \\\n",
       "0    33  BRA  Brazil     1      Acre  BR.AC      0  None  Estado     State   \n",
       "1    33  BRA  Brazil     2   Alagoas  BR.AL      0  None  Estado     State   \n",
       "2    33  BRA  Brazil     3     Amapá  BR.AP      0  None  Estado     State   \n",
       "3    33  BRA  Brazil     4  Amazonas  BR.AM      0  None  Estado     State   \n",
       "4    33  BRA  Brazil     5     Bahia  BR.BA      0  None  Estado     State   \n",
       "\n",
       "  NL_NAME_1 VARNAME_1                                           geometry  \n",
       "0      None      None  POLYGON ((-73.33251 -7.32488, -73.27482 -7.350...  \n",
       "1      None      None  MULTIPOLYGON (((-35.90153 -9.86180, -35.90153 ...  \n",
       "2      None      None  MULTIPOLYGON (((-50.02403 0.85986, -50.02403 0...  \n",
       "3      None   Amazone  POLYGON ((-67.32623 2.02968, -67.30118 1.92997...  \n",
       "4      None      Ba¡a  MULTIPOLYGON (((-38.69708 -17.97903, -38.69708...  "
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "caminho_brasil = 'C:/Users/joaovitor/Desktop/bra_adm1/BRA_adm1.shp'\n",
    "brasil = gpd.read_file(caminho_brasil)\n",
    "brasil.head()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Exibindo o mapa importado"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<AxesSubplot:>"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "brasil.plot(figsize=(15,10), edgecolor='white', linewidth=0.5, color='#CCCCCC')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Checando o crs de ambos os geodataframes"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "brasil: {'init': 'epsg:4326'}\n",
      "tabela_exemplo: {'init': 'epsg:4674'}\n"
     ]
    }
   ],
   "source": [
    "print('brasil:', brasil.crs)\n",
    "print('tabela_exemplo:', tabela_exemplo.crs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Igualando ambos os crs"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [],
   "source": [
    "tabela_exemplo.crs = brasil.crs"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Ilustrando a sobreposição de mapas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(-76.2468461036682, -26.58980665206909, -35.69767973423004, 7.215475773811342)"
      ]
     },
     "execution_count": 11,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x720 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "base = brasil.plot(figsize=(15,10), edgecolor='white', linewidth=0.5, color='#CCCCCC')\n",
    "\n",
    "mapa_exemplo = tabela_exemplo.plot(ax=base, color='red')\n",
    "mapa_exemplo.axis('off')"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gerando vários mapas"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\joaovitor\\anaconda3\\lib\\site-packages\\matplotlib\\axes\\_base.py:2571: RuntimeWarning: overflow encountered in double_scalars\n",
      "  x0, x1 = inverse_trans.transform([x0t - delta, x1t + delta])\n"
     ]
    }
   ],
   "source": [
    "for key, values in enumerate(lista_shp):\n",
    "    covid = gpd.read_file(os.path.join(caminho_covid, values))\n",
    "    covid.crs = brasil.crs\n",
    "    \n",
    "    base = brasil.plot(color='#CCCCCC', edgecolor='white', linewidth=0.5, figsize=(15,10))\n",
    "    ax = covid.plot(ax=base, color='red', markersize=13)\n",
    "    ax.axis('off')\n",
    "#===================================================================================\n",
    "    ax.set_title(f'Disseminação COVID-19\\n dia {values[9:-4]}-{values[6:8]}', \\\n",
    "                fontdict={'fontsize':'30', 'fontweight':'40'})\n",
    "    ax.annotate('Para acessar os dados: www.ufrgs.br/sig/downloads/covid19-dados/\\n Código disponível em github.com/joaotinti75',\n",
    "               xy=(0.1, .08), xycoords='figure fraction', horizontalalignment='left', \n",
    "               verticalalignment='top', fontsize=20, color='#555555')\n",
    "    base.set_axis_off()\n",
    "    plt.savefig(f'C:/Users/joaovitor/Desktop/imagens/{key+1}.png')\n",
    "    plt.close() #Para nao exibir as imagens no output, utilizo plt.close(). Consome menos memória"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Gerando o GIF"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [],
   "source": [
    "import imageio\n",
    "\n",
    "imagens = []\n",
    "caminho_imagens = 'C:/Users/joaovitor/Desktop/imagens'\n",
    "nome_arquivos = [f'{c}.png' for c in range(1, len(os.listdir(caminho_imagens))+1)]\n",
    "\n",
    "for i in nome_arquivos:\n",
    "    if i == '38.png': #caso a imagem 38 não tenha sido carregada com sucesso\n",
    "        pass\n",
    "    else:\n",
    "        imagens.append(imageio.imread(os.path.join(caminho_imagens, i)))\n",
    "    \n",
    "imageio.mimsave('C:/Users/joaovitor/Desktop/mapa.gif', imagens, duration=0.1)\n",
    "    "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": []
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}